{
 "cells": [
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-28T07:17:14.463756Z",
     "start_time": "2025-10-28T07:17:00.984276Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from sympy import acosh\n",
    "! pip install matplotlib"
   ],
   "id": "1ab3a6e1da8d7609",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting matplotlib\n",
      "  Downloading matplotlib-3.10.7-cp312-cp312-win_amd64.whl.metadata (11 kB)\n",
      "Collecting contourpy>=1.0.1 (from matplotlib)\n",
      "  Using cached contourpy-1.3.3-cp312-cp312-win_amd64.whl.metadata (5.5 kB)\n",
      "Collecting cycler>=0.10 (from matplotlib)\n",
      "  Using cached cycler-0.12.1-py3-none-any.whl.metadata (3.8 kB)\n",
      "Collecting fonttools>=4.22.0 (from matplotlib)\n",
      "  Downloading fonttools-4.60.1-cp312-cp312-win_amd64.whl.metadata (114 kB)\n",
      "Collecting kiwisolver>=1.3.1 (from matplotlib)\n",
      "  Using cached kiwisolver-1.4.9-cp312-cp312-win_amd64.whl.metadata (6.4 kB)\n",
      "Collecting numpy>=1.23 (from matplotlib)\n",
      "  Downloading numpy-2.3.4-cp312-cp312-win_amd64.whl.metadata (60 kB)\n",
      "Requirement already satisfied: packaging>=20.0 in d:\\installed_tooles\\miniconda3\\lib\\site-packages (from matplotlib) (25.0)\n",
      "Collecting pillow>=8 (from matplotlib)\n",
      "  Downloading pillow-12.0.0-cp312-cp312-win_amd64.whl.metadata (9.0 kB)\n",
      "Collecting pyparsing>=3 (from matplotlib)\n",
      "  Downloading pyparsing-3.2.5-py3-none-any.whl.metadata (5.0 kB)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in d:\\installed_tooles\\miniconda3\\lib\\site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in d:\\installed_tooles\\miniconda3\\lib\\site-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n",
      "Downloading matplotlib-3.10.7-cp312-cp312-win_amd64.whl (8.1 MB)\n",
      "   ---------------------------------------- 0.0/8.1 MB ? eta -:--:--\n",
      "   - -------------------------------------- 0.3/8.1 MB ? eta -:--:--\n",
      "   --- ------------------------------------ 0.8/8.1 MB 3.4 MB/s eta 0:00:03\n",
      "   -------------- ------------------------- 2.9/8.1 MB 6.0 MB/s eta 0:00:01\n",
      "   --------------------------- ------------ 5.5/8.1 MB 8.0 MB/s eta 0:00:01\n",
      "   -------------------------------------- - 7.9/8.1 MB 9.0 MB/s eta 0:00:01\n",
      "   ---------------------------------------- 8.1/8.1 MB 9.0 MB/s eta 0:00:00\n",
      "Using cached contourpy-1.3.3-cp312-cp312-win_amd64.whl (226 kB)\n",
      "Using cached cycler-0.12.1-py3-none-any.whl (8.3 kB)\n",
      "Downloading fonttools-4.60.1-cp312-cp312-win_amd64.whl (2.3 MB)\n",
      "   ---------------------------------------- 0.0/2.3 MB ? eta -:--:--\n",
      "   ---------------------------------------- 2.3/2.3 MB 11.7 MB/s eta 0:00:00\n",
      "Using cached kiwisolver-1.4.9-cp312-cp312-win_amd64.whl (73 kB)\n",
      "Downloading numpy-2.3.4-cp312-cp312-win_amd64.whl (12.8 MB)\n",
      "   ---------------------------------------- 0.0/12.8 MB ? eta -:--:--\n",
      "   ------- -------------------------------- 2.4/12.8 MB 12.2 MB/s eta 0:00:01\n",
      "   --------------- ------------------------ 5.0/12.8 MB 12.1 MB/s eta 0:00:01\n",
      "   ---------------------- ----------------- 7.3/12.8 MB 11.9 MB/s eta 0:00:01\n",
      "   ------------------------------ --------- 9.7/12.8 MB 12.1 MB/s eta 0:00:01\n",
      "   -------------------------------------- - 12.3/12.8 MB 12.1 MB/s eta 0:00:01\n",
      "   ---------------------------------------- 12.8/12.8 MB 11.8 MB/s eta 0:00:00\n",
      "Downloading pillow-12.0.0-cp312-cp312-win_amd64.whl (7.0 MB)\n",
      "   ---------------------------------------- 0.0/7.0 MB ? eta -:--:--\n",
      "   ------------- -------------------------- 2.4/7.0 MB 12.2 MB/s eta 0:00:01\n",
      "   ---------------------------- ----------- 5.0/7.0 MB 12.1 MB/s eta 0:00:01\n",
      "   ---------------------------------------- 7.0/7.0 MB 11.6 MB/s eta 0:00:00\n",
      "Downloading pyparsing-3.2.5-py3-none-any.whl (113 kB)\n",
      "Installing collected packages: pyparsing, pillow, numpy, kiwisolver, fonttools, cycler, contourpy, matplotlib\n",
      "\n",
      "   ---------------------------------------- 0/8 [pyparsing]\n",
      "   ----- ---------------------------------- 1/8 [pillow]\n",
      "   ----- ---------------------------------- 1/8 [pillow]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   ---------- ----------------------------- 2/8 [numpy]\n",
      "   --------------- ------------------------ 3/8 [kiwisolver]\n",
      "   -------------------- ------------------- 4/8 [fonttools]\n",
      "   -------------------- ------------------- 4/8 [fonttools]\n",
      "   -------------------- ------------------- 4/8 [fonttools]\n",
      "   -------------------- ------------------- 4/8 [fonttools]\n",
      "   -------------------- ------------------- 4/8 [fonttools]\n",
      "   ------------------------------ --------- 6/8 [contourpy]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ----------------------------------- ---- 7/8 [matplotlib]\n",
      "   ---------------------------------------- 8/8 [matplotlib]\n",
      "\n",
      "Successfully installed contourpy-1.3.3 cycler-0.12.1 fonttools-4.60.1 kiwisolver-1.4.9 matplotlib-3.10.7 numpy-2.3.4 pillow-12.0.0 pyparsing-3.2.5\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-28T07:28:06.161717Z",
     "start_time": "2025-10-28T07:28:06.112763Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 导入matplotlib库\n",
    "import matplotlib.pyplot as plt\n",
    "plt.subplots(1,1, figsize=(8, 6)) # 8英寸,72个像素 576*432\n",
    "\n",
    "# 绘制图形，散点图\n",
    "x = [1,2,3,4]\n",
    "y = [10,20,30,40]\n",
    "plt.scatter(x,y)\n",
    "plt.show()\n",
    "\n"
   ],
   "id": "initial_id",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-28T07:29:55.520400Z",
     "start_time": "2025-10-28T07:29:55.465825Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 导入matplotlib库\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.subplots(1,1, figsize=(8, 6)) # 8英寸,72个像素 576*432\n",
    "\n",
    "# 通过numpy生成数据\n",
    "x1 = np.linspace(0,10,100)\n",
    "y1 = np.sin(x1)\n",
    "plt.scatter(x1,y1)\n",
    "plt.show()\n",
    "x1\n",
    "\n"
   ],
   "id": "89e2e661e9cab230",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.1010101 ,  0.2020202 ,  0.3030303 ,  0.4040404 ,\n",
       "        0.50505051,  0.60606061,  0.70707071,  0.80808081,  0.90909091,\n",
       "        1.01010101,  1.11111111,  1.21212121,  1.31313131,  1.41414141,\n",
       "        1.51515152,  1.61616162,  1.71717172,  1.81818182,  1.91919192,\n",
       "        2.02020202,  2.12121212,  2.22222222,  2.32323232,  2.42424242,\n",
       "        2.52525253,  2.62626263,  2.72727273,  2.82828283,  2.92929293,\n",
       "        3.03030303,  3.13131313,  3.23232323,  3.33333333,  3.43434343,\n",
       "        3.53535354,  3.63636364,  3.73737374,  3.83838384,  3.93939394,\n",
       "        4.04040404,  4.14141414,  4.24242424,  4.34343434,  4.44444444,\n",
       "        4.54545455,  4.64646465,  4.74747475,  4.84848485,  4.94949495,\n",
       "        5.05050505,  5.15151515,  5.25252525,  5.35353535,  5.45454545,\n",
       "        5.55555556,  5.65656566,  5.75757576,  5.85858586,  5.95959596,\n",
       "        6.06060606,  6.16161616,  6.26262626,  6.36363636,  6.46464646,\n",
       "        6.56565657,  6.66666667,  6.76767677,  6.86868687,  6.96969697,\n",
       "        7.07070707,  7.17171717,  7.27272727,  7.37373737,  7.47474747,\n",
       "        7.57575758,  7.67676768,  7.77777778,  7.87878788,  7.97979798,\n",
       "        8.08080808,  8.18181818,  8.28282828,  8.38383838,  8.48484848,\n",
       "        8.58585859,  8.68686869,  8.78787879,  8.88888889,  8.98989899,\n",
       "        9.09090909,  9.19191919,  9.29292929,  9.39393939,  9.49494949,\n",
       "        9.5959596 ,  9.6969697 ,  9.7979798 ,  9.8989899 , 10.        ])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-28T07:57:56.424677Z",
     "start_time": "2025-10-28T07:57:56.394784Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 导入matplotlib库\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.subplots(1,1, figsize=(8, 6)) # 8英寸,72个像素 576*432\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SmiHei','Microsoft YaHei']\n",
    "\n",
    "# 绘制饼状图\n",
    "labels = ['上海','北京','四川','深证']\n",
    "size = [15,30,25,30]\n",
    "plt.pie(size,labels=labels,autopct='%1.1f%%')\n",
    "plt.show()\n"
   ],
   "id": "4ebd03bddc689568",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 18
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-28T08:02:37.797458Z",
     "start_time": "2025-10-28T08:02:37.714549Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 导入matplotlib库\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SmiHei','Microsoft YaHei']\n",
    "fig, ax = plt.subplots(1,2, figsize=(8, 6)) # 8英寸,72个像素 576*432\n",
    "\n",
    "x2 = np.linspace(0,10,100)\n",
    "y2 = np.sin(x2)\n",
    "ax[0].scatter(x2,y2)\n",
    "\n",
    "# 绘制饼状图\n",
    "labels = ['上海','北京','四川','深证']\n",
    "size = [15,30,25,30]\n",
    "ax[1].pie(size,labels=labels,autopct='%1.1f%%')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n"
   ],
   "id": "aa36a838c0fba66d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 25
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
